IN-PICTURE SEARCH ALGORITHM
Thread Rating:
  • 0 Vote(s) - 0 Average
  • 1
  • 2
  • 3
  • 4
  • 5
summer project pal
Active In SP
**

Posts: 308
Joined: Jan 2011
#1
22-01-2011, 06:13 PM


IN-PICTURE SEARCH ALGORITHM
B.Tech Seminar Report
by
Anand Babu N B
Department of Computer Science and Engineering
Government Engineering College, Thrissur
December 2010


.pdf   IN-PICTURE SEARCH ALGORITHM.pdf (Size: 321.52 KB / Downloads: 56)

Abstract
In this advanced world researchers are more interested in searching for fragments that
are similar to a query, than a total data item that is similar to a query; the search
interest is for contains, not is. This paper presents an O(log n)algorithm, called the
generalized virtual node (GVN)algorithm. The GVN algorithm is a search algorithm
for data fragments that have similar contents to that of a query. Each image is
transformed into characteristic features and these features are stored in a hierarchical
multidimensional structure, called a k-tree. The experimental results of this in-picture
search algorithm on an image database demonstrate a search quality is qualitatively
and quantitatively acceptable, with a retrieval time faster than other algorithms, such
as brute-force and Partial Matching.


Chapter 1
Introduction

Image (multimedia) data query can be classified into two different approaches:
• a-whole-picture (a-wholeobject) search
• in-picture (in-object) search
Each approach generates a different type of query result. A-whole-picture or thumbnail-
based search approach searches for data that is globally similar to the query input; on
the other hand, an in-object search approach searches for a large piece of data contains
a fragment that is similar to the query. An example of a-whole-picture search is to
find a picture in a database using the picture or its thumbnail image as a query. An
example of in-picture search is to find a picture that contains parts that are similar
to the query, where the query is a part of an image regardless what the backgrounds
are. Most of the recent work in the field of multimedia retrieval emphasizes the a-
whole-object search approach ; only a few researchers are working on in-object search
approach .

Chapter 2
K-TREE INDEX STRUCTURE

A k-tree is a directed graph.Each node has 2k incoming edges and one outgoing edge
with a balanced structure.
The structure of the k-tree is feature independent.Therefore, the positions of the
nodes in the tree are always the same, no matters what features are. Figure 2.1 shows
the comparison between using k-tree and R-tree structures as indices by using two
different features. Compared to other feature-dependent index structure (illustrated
in Figure 2.2), using the k-tree approach to search every feature altogether takes
shorter computing time than using feature-dependent structure to search on many
indices individually, merge all results,and filter them with spatial constraints.

The generalized indexing/retrieval
model

The k-tree structure is used to retain location information and a histogram is used to
store the characteristics of each portion the data that corresponds to a part of the tree.
This generalized model is depicted in Figure 3. First, either general mathematical
models, or special methods extract the feature of interest. Second, the domain of
datatype is reduced into a set and each item in the database is also mapped to the
set. Third, virtual data values are added to data items, if necessary, to create such
that each item will generate a balanced k-tree. A k-tree is built using histogram values
for each feature.

Reply
summer project pal
Active In SP
**

Posts: 308
Joined: Jan 2011
#2
22-01-2011, 06:22 PM

In-Picture Search Algorithm
ANAND BABU.N.B.
2K7705

Overview
Abstract
Introduction
K-tree index structure
R-tree index structure
Advantages and Comparison of K-tree
The Generalized Indexing/Retrieval Model
Visualisation of Retrieval Model
Virtual Node Concept
In-Picture Search Algorithm
Illustration
Conclusion


.pdf   In-Picture Search Algorithm presentation.pdf (Size: 702.06 KB / Downloads: 45)

ABSTRACT
Researchers are currently more interested in searching for fragments that are similar to a query, than a total data item that is similar to a query; the search interest is for “contains”, not “is”.
This paper presents an O(log n)algorithm, called the “generalized virtual node (GVN)”algorithm.
The GVN algorithm is a search algorithm for data fragments that have similar contents to that of a query.

INTRODUCTION
Image (multimedia) data query can be classified into two different approaches:
•a-whole-picture (a-wholeobject) search
•in-picture (in-object) search
It uses a universal model that is able to represent the characteristic features of any multimedia datatype.

K-TREE INDEX STRUCTURE
A k-tree is a directed graph.
Each node has 2k incoming edges and one outgoing edge with a balanced structure.

ADVANTAGES OF K-TREE
The structure of the k-tree is feature independent.
Since a k-tree is a hierarchical data structure, multiresolution processing can be exploited into this structure.
The complexity of data structure affects only the degree k of the tree.
The k-tree-based feature index for a feature can be used for many types of queries.
Reply

Important Note..!

If you are not satisfied with above reply ,..Please

ASK HERE

So that we will collect data for you and will made reply to the request....OR try below "QUICK REPLY" box to add a reply to this page

Quick Reply
Message
Type your reply to this message here.


Image Verification
Please enter the text contained within the image into the text box below it. This process is used to prevent automated spam bots.
Image Verification
(case insensitive)

Possibly Related Threads...
Thread Author Replies Views Last Post
  A Character Segmentation Algorithm for Printed Kannada Text Document uploader 1 1,494 10-01-2015, 12:52 PM
Last Post: zcfqmbrtb
  3D Steganography Algorithm project report helper 8 3,482 01-09-2014, 11:07 AM
Last Post: computer science crazy
  REPORT ON PID ALGORITHM VERIFICATION FOR DIFFERENT ERROR INPUT seminar projects maker 0 332 26-09-2013, 03:16 PM
Last Post: seminar projects maker
  BOYER-MOORE ALGORITHM REPORT seminar projects maker 0 405 24-09-2013, 04:29 PM
Last Post: seminar projects maker
  1. Fast algorithm for mining association rules study tips 0 331 27-08-2013, 04:45 PM
Last Post: study tips
  International Data Encryption Algorithm Report study tips 0 530 22-08-2013, 04:55 PM
Last Post: study tips
  Search Engines Work ppt study tips 0 285 22-08-2013, 03:34 PM
Last Post: study tips
  A Novel algorithm of local contrast enhancement for medical image study tips 0 386 20-08-2013, 04:33 PM
Last Post: study tips
  GRAPH SEARCH ALGORITHMS PPT study tips 0 327 16-08-2013, 04:47 PM
Last Post: study tips
  EFFICIENT MULTI-DIMENSIONAL FUZZY SEARCH FOR PERSONAL INFORMATION MANAGEMENT REPORT study tips 0 295 30-07-2013, 02:14 PM
Last Post: study tips